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Eye spy a liar: assessing the utility of eye fixations and confidence judgments for detecting concealed recognition of faces, scenes and objects

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Background - In criminal investigations, uncooperative witnesses might deny knowing a perpetrator, the location of a murder scene or knowledge of a weapon. We sought to identify markers of recognition in eye fixations and confidence judgments whilst participants told the truth and lied about recognising faces (Experiment 1) and scenes and objects (Experiment 2) that varied in familiarity. To detect recognition we calculated effect size differences in markers of recognition between familiar and unfamiliar items that varied in familiarity (personally familiar, newly learned).

Results - In Experiment 1, recognition of personally familiar faces was reliably detected across multiple fixation markers (e.g. fewer fixations, fewer interest areas viewed, fewer return fixations) during honest and concealed recognition. In Experiment 2, recognition of personally familiar non-face items (scenes and objects) was detected solely by fewer fixations during honest and concealed recognition; differences in other fixation measures were not consistent. In both experiments, fewer fixations exposed concealed recognition of newly learned faces, scenes and objects, but the same pattern was not observed during honest recognition. Confidence ratings were higher for recognition of personally familiar faces than for unfamiliar faces.

Conclusions - Robust memories of personally familiar faces were detected in patterns of fixations and confidence ratings, irrespective of task demands required to conceal recognition. Crucially, we demonstrate that newly learned faces should not be used as a proxy for real-world familiarity, and that conclusions should not be generalised across different types of familiarity or stimulus class.
Original languageEnglish
Article number38
Number of pages18
JournalCognitive Research: Principles and Implications
Issue number1
Early online date14 Aug 2020
Publication statusPublished - 1 Dec 2020


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